Feature Extraction
Transformers
PyTorch
Safetensors
English
bert
token-classification
text-embeddings-inference
Instructions to use bioscan-ml/BarcodeBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bioscan-ml/BarcodeBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="bioscan-ml/BarcodeBERT")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("bioscan-ml/BarcodeBERT") model = AutoModelForTokenClassification.from_pretrained("bioscan-ml/BarcodeBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Standardize description
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Add pipeline tag, library name, and links to paper and code (#2)
Verified signature- Add pipeline tag, library name, and links to paper and code (5345140e12f35c1e10a17f3871e820578ff1cc7f) Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>7d23648
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DOC: Update example to use BertForTokenClassification instead of AutoModel
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DOC: Blacken example code block
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DOC: Change Colab link to open a colab notebook
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Changing the call function.
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Adding max_length and padding to tokenizer and encoder.
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Create README.md
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Fixing tokenize return bug
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Fixing tokenizer return type
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Fixing encoder and tokenize functions.
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Adding automap to the tokenizer config
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Download the tokenizer from Hugging Face Hub
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Add tokenizer.py
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First version of BarcodeBERT kmer tokenizer
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Adding `safetensors` variant of this model (#1)
Verified signature- Adding `safetensors` variant of this model (315476c4fbe4e6a22f676ad404389dc4b7d194c3) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>477c08b -
First version of BarcodeBERT model (NO tokenizer.)
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initial commit
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